Biomedical imaging researchers manage large quantities of heterogeneous data, often using spreadsheets. However, limitations of spreadsheet-based systems may cause workflow challenges. We examined the data management processes of a research center at an academic hospital which manages clinical and MRI research data using spreadsheets. Through surveys, interviews, and focus groups, we characterized their workflow and needs and proposed a new centralized data management model, which includes machine learning applications for greater efficiency and research reproducibility.

Learning Objective 1: Understand current challenges in data management for a biomedical imaging research group and be able to describe possible solutions in terms of data management practices, systems, and tools.


Adriana Johnson (Presenter)
University of Pittsburgh

Jenna Schabdach, University of Pittsburgh
Lauren Rost, University of Pittsburgh
Harry Hochheiser, University of Pittsburgh

Presentation Materials: